Source: VIRGINIA POLYTECHNIC INSTITUTE submitted to NRP
MODELING FOREST GROWTH AND YIELD IN A CHANGING ENVIRONMENT
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
MCINTIRE-STENNIS
Reporting Frequency
Annual
Accession No.
0202161
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
(N/A)
Project Start Date
Jan 1, 2005
Project End Date
Dec 31, 2009
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
VIRGINIA POLYTECHNIC INSTITUTE
(N/A)
BLACKSBURG,VA 24061
Performing Department
Forest Resources and Environmental Conservation
Non Technical Summary
Forest managers have an ever-expanding array of tools available to use in managing forests. Genetic manipulations, chemical and biological pesticides and fertilizers, mechanical cultivation, burning, thinning, and pruning are some of the treatments in use. In order to make wise decisions about which tools to use, managers need models capable of quantifying forests' responses to these tools. A significant question is whether or not a model of interest is sufficiently accurate to quantify treatment responses in a meaningful way. Stated another way the question is, (quote)to what degree do model uncertainties overshadow model predictions?(quote) The same questions are relevant for all forest models, regardless of whether they predict forests responses to changes in climate, soil properties, atmospheric makeup, or management practices. To accurately characterize and minimize the uncertainties and limitations of forest ecosystem models so that the models are sufficiently accurate for their intended purposes.
Animal Health Component
75%
Research Effort Categories
Basic
25%
Applied
75%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
1230611107035%
1230613107010%
1230620209010%
1230699209010%
1320621209035%
Knowledge Area
132 - Weather and Climate; 123 - Management and Sustainability of Forest Resources;

Subject Of Investigation
0621 - Broadleaf forests of the South; 0611 - Conifer forests of the South; 0620 - Broadleaf forests of the North; 0699 - Trees, forests, and forest products, general; 0613 - Mixed conifer-broadleaf forests;

Field Of Science
2090 - Statistics, econometrics, and biometrics; 1070 - Ecology;
Goals / Objectives
The overall objective of this project is to adopt and adapt existing models to develop a system of forest growth and yield models capable of accounting for the effects of management activities and changing environmental conditions on the growth and yield of Virginias forests. In addition to providing detailed output on trees and stands that can be used to prescribe specific management activities, the models will be capable of providing landscape-level predictions to assist in regional planning decisions that involve Virginias forest resources. All models will be developed and tested using state-of-the-art methods for uncertainty assessment, calibration and sensitivity analysis (SA). Further, the models and their predictions will be supported by analyses that indicate the degree to which they are accurate or able to ascertain differences between treatment responses or changes in environment.
Project Methods
Research procedures will emphasize data compilation and analysis, information synthesis, statistical and computer modeling, model evaluation and updating, and model application to forest management and decision support. Effort will be directed to primary data collection only when essential information needed to address project objectives is lacking. Analysis and synthesis of existing knowledge and data provides a cost-effective way of acquiring information and using it to address practical concerns. Statistical and computer modeling are the basic tools of information synthesis. They provide means to explain and communicate relationships, and to make objective predictions to meet the project goals. Model evaluation will include activities such as model calibration, SA and uncertainty assessment, which are essential to understanding the performance of models and validity of their predictions. Model application will provide quantitative answers to aid policy and management decisions.

Progress 01/01/05 to 12/31/09

Outputs
OUTPUTS: A significant output of the project was the accuracy assessment and augmentation of the Forest Vegetation Simulator, Southern Variant (FVS-Sn), for Southeastern Appalachian hardwood forests. By testing the model against long-term permanent forest inventory plots, baseline accuracy statistics were generated for FVS-Sn predictions. By modifying and refitting the tree mortality model in FVS-Sn, 4 percent to 7 percent gains in prediction accuracy were realized. Another significant output was the implementation of the southeastern hardwood regeneration model, REGEN. The implementation allows users to make rapid predictions of forest regeneration conditions that can be linked to existing databases and computer models of forest growth and yield. The outputs of this study were delivered to the U.S. Forest Service for eventual implementation into the FVS modeling system. Further, they were disseminated through presentations at public conferences and symposia, and distributed via the web through the project leader's web site at http://www.frec.vt.edu. PARTICIPANTS: Students working on this project included the following: Nathan D. Herring, M.S. (2007) in Forestry; Kevin C. Packard, Ph.D. (2008) in Forestry; and Huei-in Wang Ph.D. (expected 2010) in Forestry. Partner organizations included the following: U.S. Forest Service Washington Office, Forest Management Service Center (detached) Fort Collins, Colorado; the U.S. Forest Service, Southern Research Station, Research Work Unit, 4101 Southern Appalachian Forests, Asheville, North Carolina; and Rocky Mountain Research Station, work unit 4101, Forestry Sciences Laboratory, Moscow, Idaho; Appalachian Hardwood Manufacturers, Inc. High Point, North Carolina. TARGET AUDIENCES: The target audience for this work included Forest Service managers and researchers who require accurate projections of forest growth and yield in natural mixed species forests of the Southern Appalachian Mountains in the southeastern United States. Another primary target was the audience of state and private forest managers and consultants who provide management services to non-public industrial and non-industrial forest landowners in the Southeast. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
The outputs of this project led from changes in knowledge of inaccuracies in existing growth and yield models, plus changes in actions that eliminated modeling errors. As a result, conditions have changed whereby users of FVS-Sn can achieve improved accuracy in their model predictions. The primary gains in knowledge centered on first identifying the magnitude of prediction errors in baseline model predictions, followed by investigations that identified possible errors in data or mechanisms in the FVS-Sn model that could be modified to increase prediction accuracy. Finally, through further testing and implementation, the new knowledge gained here was put into action through a series of modifications to FVS-Sn involving updating regression coefficients and threshold parameters used by the model in its projection cycles. Users of FVS-Sn can expect increases of 4 to 7 percent in prediction accuracy in growth modeling applications in mixed hardwood forests in the Southeastern United States.

Publications

  • Radtke, P.J., Amateis, R.L., Prisley, S.P., Copenheaver, C.A., Chojnacky, D.C., Pittman, J.R., and H.E. Burkhart. 2009. Modeling production and decay of coarse woody debris in loblolly pine plantations. Forest Ecology and Management 257(3):790-799.
  • Radtke, P.J., Boland, H.T., and G. Scaglia. 2010 An evaluation of overhead laser scanning to estimate herbage removals in pasture quadrats. Agricultural and Forest Meteorology 150:1523-1528.


Progress 10/01/08 to 09/30/09

Outputs
OUTPUTS: Compilation and analysis of long-term experimental data on loblolly pine responses to intensive management. Development of loblolly pine decision support system that produces outputs for ecological and economic analysis, including carbon sequestration outputs. Annual field tour of pine management research sites for forestry students, private landowners, and research cooperators. Accuracy assessment of Forest Vegetation Simulator (FVS) to quantify baseline accuracy, identify key sensitivities, and reduce prediction uncertainty, thus increasing confidence in model predictions. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Growth and yield prediction technology developed under this project has been adopted by thousands of private landowners to adapt traditional management practices in southern pine forests in response to increased concern for carbon sequestration, bioenergy production, and constraints due to the economic downturn. Model development efforts are being adopted by the USDA Forest Service to support and augment its Forest Vegetation Simulator (FVS) modeling system, the primary model used to project growth and yield for planning and management in National Forests forests of the eastern United States.

Publications

  • Amateis, R. L., H. E. Burkhart and C. A. Carlson. 2009. Does row orientation affect the growth of loblolly pine plantations South. J. Appl. For. 33:77-80.
  • Carlson, C. A., T. R. Fox, H. E. Burkhart, H. L. Allen and T. J. Albaugh. 2009. Accuracy of subsampling for height measurements in loblolly pine plots. South. J. Appl. For. 33:145-149.
  • Radtke, P. J., R. L. Amateis, S. P. Prisley, C. A. Copenheaver, D. C. Chojnacky, J. R. Pittman and H. E. Burkhart. 2009. Modeling production and decay of coarse woody debris in loblolly pine. For. Ecol. and Manage. 257:790-799.
  • Russell, M. B., H. E. Burkhart and R. L. Amateis. 2009. Biomass partitioning in a miniature-scale loblolly pine spacing trial. Can. J. For. Res. 39:320-329.
  • Trincado, G. and H. E. Burkhart. 2009. A framework for modeling the dynamics of first-order branches and spatial distribution of knots in loblolly pine trees. Can. J. For. Res. 39:566-579.
  • Burkhart, H. E. 2008. Modelling growth and yield for intensively managed forests. Jour. For. Sci. 24:173-180.
  • Carlson, C. A., H. E. Burkhart, H. L. Allen and T. R. Fox. 2008. Absolute and relative changes in tree growth rates and changes to the stand diameter distribution of Pinus taeda as a result of midrotation fertilizer applications. Can. J. For. Res. 38:2063-2071.
  • Choi, J., H. E. Burkhart and R. L. Amateis. 2008. Modeling trends in stem quality characteristics of loblolly pine trees in unthinned plantations. Can. J. For. Res. 38:1446-1457.
  • Mehtatalo, L., T. G. Gregoire and H. E. Burkhart. 2008. Comparing strategies for modeling tree diameter percentiles from remeasured plots. Environmetrics 19:529-548.
  • Russell, M. B. 2008. Modeling the biomass partitioning of loblolly pine grown in a miniature-scale plantation. M.S. thesis. Department of Forestry, Virginia Polytechnic Institute and State University, Blacksburg, VA.
  • Trincado, G. and H. E. Burkhart. 2008. A model of knot shape and volume in loblolly pine trees. Wood and Fiber Sci. 40:634-646.
  • VanderSchaaf, C. L. and H. E. Burkhart. 2008. Using segmented regression to estimate stages and phases of stand development. For. Sci. 54:167-175.


Progress 10/01/07 to 09/30/08

Outputs
OUTPUTS: 1) Completed an 18 month program to review models of Appalachian hardwood growth and yield, funded by the Appalachian Hardwood Forest Research Alliance, a research arm of Appalachian Hardwood Manufacturing, Inc. 2) Completed year 3 of a four-year program aimed at the comprehensive evaluation of the USDA Forest Service "Forest Vegetation Simulator - Southern Variant" growth and yield model (FVS-Sn). 3) Published results of a forest inventory protocol for rapid wood content and growth assessment in mixed-species forests. 5) Continued development of site-quality classification system for FVS-Sn based on site and forest attributes derived from public-domain geospatial and forest inventory data sets. Presented work at the Soil Science Society of America conference, November 4-8, 2007, in New Orleans. 6) Completed southwide compilation of wildfire risk and fuel accumulation models for extension to the FVS-Sn model. Compiled fuel-loading and size distribution parameters for six forest types in southern U.S. forests to be incorporated into FVS-Sn by the Forest Service. PARTICIPANTS: Appalachian Hardwood Manufacturers, Inc., PO Box 427, High Point, NC 27261-0427 TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Modeling results are being applied by corporate managers to over 8 million hectares of forest land with significant improvements in profitability. In addition, thousands of private landowners are reaping substantial benefits as they use these results to improve profits and to reach other management goals for their lands.

Publications

  • Packard, K.C. and P. J. Radtke. 2008. Forest sampling combining fixed- and variable-radius sample plots. Canadian Journal of Forest Research, 37:1460-1471.


Progress 10/01/06 to 09/30/07

Outputs
OUTPUTS: 1) Continued an 18 month program to review models of Appalachian hardwood growth and yield, funded by the Appalachian Hardwood Forest Research Alliance, a research arm of Appalachian Hardwood Manufacturing, Inc. 2) Completed year 2 of a three-year program aimed at the comprehensive evaluation of the USDA Forest Service "Forest Vegetation Simulator - Southern Variant" growth and yield model (FVS-Sn). Cataloged distribution information for more than 2300 FVS-Sn model parameters for southern Appalachian hardwood forests. Completed sensitivity analysis of FVS-Sn for southern Appalachian oak-hickory forest type. Presented results of sensitivity analysis at the Third Forest Vegetation Simulator (FVS) Conference, February 13-15, 2007, in Fort Collins Colorado. 3) Developed and published results of a forest inventory protocol for rapid wood content and growth assessment in mixed-species forests. 4) Developed statistical point-process models for simulating tree-location patterns in forest growth models. Presented work at the conference on Complex Stand Structures and Associated Dynamics: measurement indices and modeling, July 29-August 2, 2007, in Sault Ste. Marie, Ontario. 5) Began development of site-quality classification system for FVS-Sn based on site and forest attributes derived from public-domain geospatial and forest inventory data sets. Presented work at the Soil Science Society of America conference, November 4-8, 2007, in New Orleans. 6) Hosted a June, 2007 workshop of federal and academic partners (USDA Forest Service Forest Management Service Center, collaborators) for development of wildfire risk and fuel accumulation extensions to the FVS-Sn model. Compiled fuel-loading and size distribution parameters for six forest types in southern U.S. forests to be incorporated into FVS-Sn by the Forest Service. PARTICIPANTS: Appalachian Hardwood Manufacturers Incorporated, PO Box 427, High Point, NC 27261-0427

Impacts
Modeling results are being applied by corporate managers to over 8 million hectares of forest land with significant improvements in profitability. In addition, thousands of private landowners are reaping substantial benefits as they use these results to improve profits and to reach other management goals for their lands.

Publications

  • Burkhart, H. E. 2007. An overview of options for modeling complex stand structures. In: Complex Stand Structures and Associated Dynamics: Measurement Indices and Modeling Approaches. Ontario Forest Research Institute, Forest Research Information Paper 167. Sault Ste. Marie, Ontario. pp. 72-73.
  • Choi, J., Y. Byung-Oh and H. E. Burkhart. 2007. Allometry, basal area growth and volume equations for Quercus mongolica and Quercus variabilis in Gangwon Province of Korea. Journal of Korean Forest Society 96(2):189-196.
  • Choi, J., T. R. Fox and H. E. Burkhart. 2007. Sustainability of pine plantations in the United States. In: Proc. 2007 Annual Meeting of the Korean Forest Society. pp. 55-56.
  • Henning, J. G. and P. J. Radtke. 2007. Ground-based laser imaging for assessing three-dimensional forest canopy structure. Photogrammetric Engineering and Remote Sensing, 72:1349-1358.
  • Packard, K.C. and P. J. Radtke. 2007. Forest sampling combining fixed- and variable-radius sample plots. Canadian Journal of Forest Research, 37:1460-1471.
  • Sharma, M., H. E. Burkhart and R. L. Amateis. 2007. Scaling taper relationships from miniature-scale to operational-scale stands of loblolly pine. Forest Science 53(5):611-617.
  • Trincado, G., C. L. VanderSchaaf and H. E. Burkhart. 2007. Regional mixed-effects height-diameter models for loblolly pine (Pinus taeda L.) plantations. Eur. J. For. Res. 126:253-262.
  • VanderSchaaf, C. L. and H. E. Burkhart. 2007. Comparison of methods to estimate Reineke's maximum size-density relationship species boundary line slope. Forest Science 53(3)435-442.
  • VanderSchaaf, C. L. 2006. Modeling maximum size-density relationships of loblolly pine (Pinus taeda L.) plantations. Ph.D. Dissertation, Department of Forestry, Virginia Polytechnic Institute and State University, Blacksburg, VA.


Progress 10/01/05 to 09/30/06

Outputs
1) Initiated a one-year program to review models of Appalachian hardwood growth and yield, funded by the Appalachian Hardwood Forest Research Alliance, a research arm of Appalachian Hardwood Manufacturing, Inc., 2) Completed year 1 of a three-year program aimed at the comprehensive evaluation of the USDA Forest Service "Forest Vegetation Simulator - Southern Variant" growth and yield model (FVS-Sn). Assembled resources and personnel to accomplish the program objectives. Hosted a 2-day workshop (November, 14-15th, 2005) on "Development and implementation of the FVS-Sn for mixed hardwoods in the Southeast," attended by Forest Service and Virginia Tech university cooperators. Compiled distribution information for more than 2300 FVS-Sn model parameters for southern Appalachian hardwood forests. Completed modifications to FVS-Sn software for computationally-intense analyses. Completed preliminary sensitivity analysis of FVS-Sn large-tree diameter growth model. 3) Developed individual tree models of wood decay and nutrient composition following natural mortality in loblolly pine plantations. Scaled individual tree predictions to stand-level and validated model predictions from Alabama Forest Inventory and Analysis Phase III data. 4) Co-hosted the Southern Mensurationists Conference, October 10-13th 2006, Charleston, SC, with sponsorship from ArborGen LLC and MeadWestvaco Inc. Invited talks included subjects of clonal plantations of loblolly pine; plantation forestry for bioenergy and biofuels; intensive plantation silviculture including mid-rotation thinning and fertilization; wildfire risk and fuel accumulation in southern forests; and uncertainty in predicting growth and yield of natural hardwood forests in the Southern Appalachians 5) Successfully proposed to host a March, 2007 meeting of federal and academic partners for development of wildfire risk and fuel accumulation models in southern forests.

Impacts
Modeling results are being applied by corporate managers to over 8 million hectares of forest land with significant improvements in profitability. In addition, thousands of private landowners are reaping substantial benefits as they use these results to improve profits and to reach other management goals for their lands.

Publications

  • Henning, J. G. and P. J. Radtke. 2006. Detailed stem measurements of standing trees from ground-based scanning LiDAR. Forest Science 52:67-80.
  • Radtke, P. J. and A. P. Robinson. 2006. A Bayesian strategy for combining predictions from empirical and process-based models. Ecological Modelling 190:287-298.
  • Dieguez-Aranda, U., H. E. Burkhart and R. L. Amateis. 2006. Dominant height growth of unthinned loblolly pine (Pinus taeda L.) plantations in the United States. For. Sci. 52:262-272.
  • Sharma, M., M. Smith, H. E. Burkhart and R. L. Amateis. 2006. Modeling the impact of thinning on height development of dominant and condominant loblolly pine trees. Ann. For. Sci. 63:349-354.
  • Amateis, R. L. and H. E. Burkhart. 2006. Growth following pruning of young loblolly pine trees: Some early results. In: Connor, K. F., ed. Porc. 13th Biennial Southern Silvicultural Research Conference. Gen. Tech. Rep. SRS-92. USDA For. Serv. Southern Research Station. pp. 42-44.
  • Amateis, R. L., H. E. Burkhart, S. P. Prisley and J. Liu. 2006. The effect of physiographic region and geographic locale on predicting the dominant height and basal area of loblolly pine plantations. S. Jour. Appl. For. 30(3):147-153.
  • Trincado, G. 2006. Dynamic modeling of branches and knot formation in loblolly pine (Pinus taeda L.) trees. Ph.D. Dissertation. Department of Forestry, Virginia Polytechnic Institute and State University, Blacksburg, VA.
  • Sharma, M., H. E. Burkhart and R.L. Amateis. 2006. Scaling taper relationships from seedlings to mature trees. Loblolly Pine Growth and Yield Research Cooperative Report No. 146. Department of Forestry, Virginia Polytechnic Institute and State University, Blacksburg, VA.
  • Burkhart, H.E. and R.L. Amateis. 2006. 2006 Annual Report. Loblolly Pine Growth and Yield Research Cooperative Report No. 147. Department of Forestry, Virginia Polytechnic Institute and State University, Blacksburg, VA.
  • Choi, J. 2006. Loblolly pine growth and yield cooperative in the USA. Forest 2006(1):76-80.


Progress 10/01/04 to 09/30/05

Outputs
Developments were aimed in three fronts, 1) ascertaining the needs of companies and agencies in the Southeastern U.S. for models and information relating to forest management, 2) obtaining data sets and working computer models for subsequent linkage, augmentation and evaluation, and 3) statistical modeling of forest growth and yield. Modeling and information needs were assessed through communication with members of two agency-industry-university cooperatives, the Loblolly Pine Growth and Yield Research Cooperative at Virginia Tech, and the Appalachian Hardwood Forest Research Alliance. Specific knowledge gaps were identified in the following growth and yield modeling areas: clonal plantations of loblolly pine; plantation forestry for bioenergy and biofuels; intensive plantation silviculture including mid-rotation thinning and fertilization; wildfire risk and fuel accumulation in southern forests; and uncertainty in predicting growth and yield of natural hardwood forests in the Southern Appalachians. Twelve hardwood data sets were identified from MeadWestvaco hardwood research division for their potential use in this project. Two of them were transferred to Virginia Tech for ongoing collaborative model evaluation efforts with Mead Westvaco personnel. An extensive data set of loblolly pine coarse woody material was obtained from the Loblolly Pine Growth and Yield Research Cooperative to assess the potential of developing fire risk and fuel accumulation models. Computer models including the USDA Forest Service Southern Variant Forest Vegetation Simulator, the NASA C-QUEST model, and the PTAEDA3 and FASTLOB loblolly pine growth models were identified as candidates for further augmentation and evaluation. Statistical modeling primarily made progress in areas of characterizing the effects of management on forest growth and yield for loblolly pine and other forest populations of interest to U.S. forest managers.

Impacts
We identified several key knowledge gaps to be addressed by future updates and evaluations of existing growth and yield models. By involving a range of industry, agency, and university personnel in this process, we ensured that these gaps will be met using the best available data, models, methods and personnel. Progress was made by developing statistical models of relationships between management activities and forest growth. These modeling results are being applied by corporate managers to over 8 million hectares of forest land with a significant improvement in profitability. In addition, thousands of private landowners are reaping substantial benefits as they use these results to improve profits and to reach other management goals for their lands.

Publications

  • Amateis, R. L. and H. E. Burkhart. 2005. The influence of thinning on the proportion of peeler, sawtimber, and pulpwood trees in loblolly pine plantations. Southern Journal of Applied Forestry 29:158-162.
  • Bullock, B. P. and H. E. Burkhart. 2005. An evaluation of spatial dependency in juvenile loblolly pine stands using stem diameter. Forest Science 51:102-108.
  • Bullock, B. P. and H. E. Burkhart. 2005. Juvenile diameter distributions of loblolly pine characterized by the two-parameter Weibull function. New Forests 29:233-244.
  • Dieguez-Aranda, U., H. E. Burkhart and R. Rodriguez-Soalleiro. 2005. Modeling dominant height growth of radiata pine (Pinus radiata D. Don) plantations in north-western Spain. Forest Ecology and Management 215:271-284.
  • Henning, J. G. 2005. Modeling forest canopy distribution from ground-based laser scanning data. Ph.D. dissertation, Virginia Tech Department of Forestry, Blacksburg, VA. 171 p.
  • Westfall, J. A., H. E. Burkhart and H. L. Allen. 2004. Young stand growth modeling for intensively-managed loblolly pine plantations in southeastern US. Forest Science 50:823-835.